activity
20192022
most citedCondition-Transforming Variational AutoEncoder for Conversation Response Generation

2 citations · 8 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CL2022

Feature Aggregation in Zero-Shot Cross-Lingual Transfer Using Multilingual BERT

Beiduo Chen, Wu Guo, Quan Liu +1

Multilingual BERT (mBERT), a language model pre-trained on large multilingual corpora, has impressive zero-shot cross-lingual transfer capabilities and performs surprisingly well o…

cs.CL2022

Multi-Level Contrastive Learning for Cross-Lingual Alignment

Beiduo Chen, Wu Guo, Bin Gu +2

Cross-language pre-trained models such as multilingual BERT (mBERT) have achieved significant performance in various cross-lingual downstream NLP tasks. This paper proposes a multi…

cs.CL20212 cited

Detecting Speaker Personas from Conversational Texts

Jia-Chen Gu, Zhen-Hua Ling, Yu Wu +3

Personas are useful for dialogue response prediction. However, the personas used in current studies are pre-defined and hard to obtain before a conversation. To tackle this issue,…

cs.CL20212 cited

SemEval-2021 Task 4: Reading Comprehension of Abstract Meaning

Boyuan Zheng, Xiaoyu Yang, Yu-Ping Ruan +4

This paper introduces the SemEval-2021 shared task 4: Reading Comprehension of Abstract Meaning (ReCAM). This shared task is designed to help evaluate the ability of machines in re…

cs.CL2020

Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots

Jia-Chen Gu, Tianda Li, Quan Liu +4

In this paper, we study the problem of employing pre-trained language models for multi-turn response selection in retrieval-based chatbots. A new model, named Speaker-Aware BERT (S…

cs.CL2019

Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based Chatbots

Jia-Chen Gu, Zhen-Hua Ling, Xiaodan Zhu +1

This paper proposes a dually interactive matching network (DIM) for presenting the personalities of dialogue agents in retrieval-based chatbots. This model develops from the intera…